Dynamic Contrast-Enhanced Computed Tomography Imaging Biomarkers Correlated With Immunohistochemistry for Monitoring the Effects of Sorafenib on Experimental Prostate Carcinomas
Bibliographic record
Abstract
OBJECTIVES: To investigate dynamic contrast-enhanced computed tomography (DCE-CT) for monitoring the effects of sorafenib on experimental prostate carcinomas in rats by quantitative assessments of tumor microcirculation parameters with immunohistochemical validation. MATERIAL AND METHODS: Prostate carcinoma allografts (MLLB-2) implanted subcutaneously in male Copenhagen rats (n=16) were imaged at baseline and after a 1-week treatment course of sorafenib using DCE-CT with iopromide (Ultravist 370, Bayer Pharma, Berlin, Germany) on a dual-source 128-slice CT (Somatom Definition FLASH, Siemens Healthcare, Forchheim, Germany). Scan parameters were as follows: detector width, 38.4 mm; contrast agent volume, 2 mL/kg bodyweight; injection rate, 0.5 mL/s; scan duration, 90 seconds; and temporal resolution, 0.5 seconds. The treatment group (n=8) received daily applications of sorafenib (10 mg/kg bodyweight) via gavage. Quantitative parameters of tumor microcirculation (plasma flow, mL/100 mL/min), endothelial permeability-surface area product (PS, mL/100 mL/min), and tumor vascularity (plasma volume, %) were calculated using a 2-compartment uptake model. DCE-CT parameters were correlated with immunohistochemical assessments of tumor vascularity (RECA-1), cell proliferation (Ki-67), and apoptosis (TUNEL). RESULTS: Sorafenib significantly (P < 0.05) suppressed tumor perfusion (25.1 ± 9.8 to 9.5 ± 6.0 mL/100 mL/min), tumor vascularity (15.6% ± 11.4% to 5.4% ± 2.1%), and PS (8.7 ± 4.5 to 2.7 ± 2.5 mL/100 mL/min) in prostate carcinomas during the treatment course. Immunohistochemistry revealed significantly lower tumor vascularity in the therapy group than in the control group (RECA-1; 181 ± 24 vs. 314 ± 47; P < 0.05). In sorafenib-treated tumors, significantly more apoptotic cells (TUNEL; 7132 ± 3141 vs. 3722 ± 1445; P < 0.05) and significantly less proliferating cells (Ki-67; 9628 ± 1.298 vs. 17,557 ± 1446; P < 0.05) were observed than those in the control group. DCE-CT tumor perfusion correlated significantly (P < 0.05) with tumor cell proliferation (Ki-67; r=0.55). DCE-CT tumor vascularity correlated significantly (P < 0.05) with immunohistochemical tumor cell apoptosis (TUNEL; r=-0.59) and tumor cell proliferation (Ki-67; r=0.68). DCE-CT endothelial PS correlated significantly (P < 0.05) with immunohistochemical tumor cell apoptosis (TUNEL; r=-0.6) and tumor vascularity (RECA-1; r=0.53). While performing corrections for multiple comparisons, we observed a significant correlation only between DCE-CT tumor vascularity (RECA-1) and tumor cell proliferation (Ki-67). CONCLUSION: Sorafenib significantly suppressed tumor perfusion, tumor vascularity, and PS quantified by DCE-CT in experimental prostate carcinomas in rats. These functional CT surrogate markers showed moderate correlations with antiangiogenic, antiproliferative, and proapoptotic effects observed by immunohistochemistry. DCE-CT may be applicable for the quantification of noninvasive imaging biomarkers of therapy response to antiangiogenic therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".